{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "os.chdir(\"../..\") "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "********************\n",
      "\n",
      "   Going to generate c302_C2_AVB_DB and run for 4000 on jNeuroML_NEURON\n",
      "\n",
      "********************\n",
      "Set default parameters for C\n",
      "Set default parameters for C2\n",
      "Opened file: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/../../../herm_full_edgelist.csv\n",
      "Opened file: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/../../../herm_full_edgelist.csv\n",
      "c302      >>>  Positioning muscle: MDR01 at (80,-270,80)\n",
      "c302      >>>  Positioning muscle: MDR02 at (80,-240,80)\n",
      "c302      >>>  Positioning muscle: MDR03 at (80,-210,80)\n",
      "c302      >>>  Positioning muscle: MDR04 at (80,-180,80)\n",
      "c302      >>>  Positioning muscle: MDR05 at (80,-150,80)\n",
      "c302      >>>  Positioning muscle: MDR06 at (80,-120,80)\n",
      "c302      >>>  Positioning muscle: MDR07 at (80,-90,80)\n",
      "c302      >>>  Positioning muscle: MDR08 at (80,-60,80)\n",
      "c302      >>>  Positioning muscle: MDR09 at (80,-30,80)\n",
      "c302      >>>  Positioning muscle: MDR10 at (80,0,80)\n",
      "c302      >>>  Positioning muscle: MDR11 at (80,30,80)\n",
      "c302      >>>  Positioning muscle: MDR12 at (80,60,80)\n",
      "c302      >>>  Positioning muscle: MDR13 at (80,90,80)\n",
      "c302      >>>  Positioning muscle: MDR14 at (80,120,80)\n",
      "c302      >>>  Positioning muscle: MDR15 at (80,150,80)\n",
      "c302      >>>  Positioning muscle: MDR16 at (80,180,80)\n",
      "c302      >>>  Positioning muscle: MDR17 at (80,210,80)\n",
      "c302      >>>  Positioning muscle: MDR18 at (80,240,80)\n",
      "c302      >>>  Positioning muscle: MDR19 at (80,270,80)\n",
      "c302      >>>  Positioning muscle: MDR20 at (80,300,80)\n",
      "c302      >>>  Positioning muscle: MDR21 at (80,330,80)\n",
      "c302      >>>  Positioning muscle: MDR22 at (80,360,80)\n",
      "c302      >>>  Positioning muscle: MDR23 at (80,390,80)\n",
      "c302      >>>  Positioning muscle: MDR24 at (80,420,80)\n",
      "c302      >>>  Positioning muscle: MVR01 at (-80,-270,80)\n",
      "c302      >>>  Positioning muscle: MVR02 at (-80,-240,80)\n",
      "c302      >>>  Positioning muscle: MVR03 at (-80,-210,80)\n",
      "c302      >>>  Positioning muscle: MVR04 at (-80,-180,80)\n",
      "c302      >>>  Positioning muscle: MVR05 at (-80,-150,80)\n",
      "c302      >>>  Positioning muscle: MVR06 at (-80,-120,80)\n",
      "c302      >>>  Positioning muscle: MVR07 at (-80,-90,80)\n",
      "c302      >>>  Positioning muscle: MVR08 at (-80,-60,80)\n",
      "c302      >>>  Positioning muscle: MVR09 at (-80,-30,80)\n",
      "c302      >>>  Positioning muscle: MVR10 at (-80,0,80)\n",
      "c302      >>>  Positioning muscle: MVR11 at (-80,30,80)\n",
      "c302      >>>  Positioning muscle: MVR12 at (-80,60,80)\n",
      "c302      >>>  Positioning muscle: MVR13 at (-80,90,80)\n",
      "c302      >>>  Positioning muscle: MVR14 at (-80,120,80)\n",
      "c302      >>>  Positioning muscle: MVR15 at (-80,150,80)\n",
      "c302      >>>  Positioning muscle: MVR16 at (-80,180,80)\n",
      "c302      >>>  Positioning muscle: MVR17 at (-80,210,80)\n",
      "c302      >>>  Positioning muscle: MVR18 at (-80,240,80)\n",
      "c302      >>>  Positioning muscle: MVR19 at (-80,270,80)\n",
      "c302      >>>  Positioning muscle: MVR20 at (-80,300,80)\n",
      "c302      >>>  Positioning muscle: MVR21 at (-80,330,80)\n",
      "c302      >>>  Positioning muscle: MVR22 at (-80,360,80)\n",
      "c302      >>>  Positioning muscle: MVR23 at (-80,390,80)\n",
      "c302      >>>  Positioning muscle: MVL01 at (-80,-270,-80)\n",
      "c302      >>>  Positioning muscle: MVL02 at (-80,-240,-80)\n",
      "c302      >>>  Positioning muscle: MVL03 at (-80,-210,-80)\n",
      "c302      >>>  Positioning muscle: MVL04 at (-80,-180,-80)\n",
      "c302      >>>  Positioning muscle: MVL05 at (-80,-150,-80)\n",
      "c302      >>>  Positioning muscle: MVL06 at (-80,-120,-80)\n",
      "c302      >>>  Positioning muscle: MVL07 at (-80,-90,-80)\n",
      "c302      >>>  Positioning muscle: MVL08 at (-80,-60,-80)\n",
      "c302      >>>  Positioning muscle: MVL09 at (-80,-30,-80)\n",
      "c302      >>>  Positioning muscle: MVL10 at (-80,0,-80)\n",
      "c302      >>>  Positioning muscle: MVL11 at (-80,30,-80)\n",
      "c302      >>>  Positioning muscle: MVL12 at (-80,60,-80)\n",
      "c302      >>>  Positioning muscle: MVL13 at (-80,90,-80)\n",
      "c302      >>>  Positioning muscle: MVL14 at (-80,120,-80)\n",
      "c302      >>>  Positioning muscle: MVL15 at (-80,150,-80)\n",
      "c302      >>>  Positioning muscle: MVL16 at (-80,180,-80)\n",
      "c302      >>>  Positioning muscle: MVL17 at (-80,210,-80)\n",
      "c302      >>>  Positioning muscle: MVL18 at (-80,240,-80)\n",
      "c302      >>>  Positioning muscle: MVL19 at (-80,270,-80)\n",
      "c302      >>>  Positioning muscle: MVL20 at (-80,300,-80)\n",
      "c302      >>>  Positioning muscle: MVL21 at (-80,330,-80)\n",
      "c302      >>>  Positioning muscle: MVL22 at (-80,360,-80)\n",
      "c302      >>>  Positioning muscle: MVL23 at (-80,390,-80)\n",
      "c302      >>>  Positioning muscle: MVL24 at (-80,420,-80)\n",
      "c302      >>>  Positioning muscle: MDL01 at (80,-270,-80)\n",
      "c302      >>>  Positioning muscle: MDL02 at (80,-240,-80)\n",
      "c302      >>>  Positioning muscle: MDL03 at (80,-210,-80)\n",
      "c302      >>>  Positioning muscle: MDL04 at (80,-180,-80)\n",
      "c302      >>>  Positioning muscle: MDL05 at (80,-150,-80)\n",
      "c302      >>>  Positioning muscle: MDL06 at (80,-120,-80)\n",
      "c302      >>>  Positioning muscle: MDL07 at (80,-90,-80)\n",
      "c302      >>>  Positioning muscle: MDL08 at (80,-60,-80)\n",
      "c302      >>>  Positioning muscle: MDL09 at (80,-30,-80)\n",
      "c302      >>>  Positioning muscle: MDL10 at (80,0,-80)\n",
      "c302      >>>  Positioning muscle: MDL11 at (80,30,-80)\n",
      "c302      >>>  Positioning muscle: MDL12 at (80,60,-80)\n",
      "c302      >>>  Positioning muscle: MDL13 at (80,90,-80)\n",
      "c302      >>>  Positioning muscle: MDL14 at (80,120,-80)\n",
      "c302      >>>  Positioning muscle: MDL15 at (80,150,-80)\n",
      "c302      >>>  Positioning muscle: MDL16 at (80,180,-80)\n",
      "c302      >>>  Positioning muscle: MDL17 at (80,210,-80)\n",
      "c302      >>>  Positioning muscle: MDL18 at (80,240,-80)\n",
      "c302      >>>  Positioning muscle: MDL19 at (80,270,-80)\n",
      "c302      >>>  Positioning muscle: MDL20 at (80,300,-80)\n",
      "c302      >>>  Positioning muscle: MDL21 at (80,330,-80)\n",
      "c302      >>>  Positioning muscle: MDL22 at (80,360,-80)\n",
      "c302      >>>  Positioning muscle: MDL23 at (80,390,-80)\n",
      "c302      >>>  Positioning muscle: MDL24 at (80,420,-80)\n",
      "AVBL-AVBR 6 exc Acetylcholine\n",
      "AVBR-AVBL 2 exc Acetylcholine\n",
      "AVBR-DB4 1 exc Acetylcholine\n",
      "AVBL-AVBR_GJ 17 exc Generic_GJ\n",
      "AVBL-DB2_GJ 4 exc Generic_GJ\n",
      "AVBL-DB3_GJ 9 exc Generic_GJ\n",
      "AVBL-DB4_GJ 4 exc Generic_GJ\n",
      "AVBL-DB5_GJ 3 exc Generic_GJ\n",
      "AVBL-DB6_GJ 4 exc Generic_GJ\n",
      "AVBL-DB7_GJ 13 exc Generic_GJ\n",
      "AVBR-AVBL_GJ 17 exc Generic_GJ\n",
      "AVBR-DB1_GJ 15 exc Generic_GJ\n",
      "AVBR-DB2_GJ 3 exc Generic_GJ\n",
      "AVBR-DB3_GJ 2 exc Generic_GJ\n",
      "AVBR-DB4_GJ 5 exc Generic_GJ\n",
      "AVBR-DB5_GJ 4 exc Generic_GJ\n",
      "AVBR-DB6_GJ 3 exc Generic_GJ\n",
      "AVBR-DB7_GJ 3 exc Generic_GJ\n",
      "DB1-AVBR_GJ 15 exc Generic_GJ\n",
      "DB1-DB2_GJ 5 exc Generic_GJ\n",
      "DB2-AVBL_GJ 4 exc Generic_GJ\n",
      "DB2-AVBR_GJ 3 exc Generic_GJ\n",
      "DB2-DB1_GJ 5 exc Generic_GJ\n",
      "DB2-DB3_GJ 14 exc Generic_GJ\n",
      "DB3-AVBL_GJ 9 exc Generic_GJ\n",
      "DB3-AVBR_GJ 2 exc Generic_GJ\n",
      "DB3-DB2_GJ 14 exc Generic_GJ\n",
      "DB3-DB4_GJ 1 exc Generic_GJ\n",
      "DB4-AVBL_GJ 4 exc Generic_GJ\n",
      "DB4-AVBR_GJ 5 exc Generic_GJ\n",
      "DB4-DB3_GJ 1 exc Generic_GJ\n",
      "DB4-DB5_GJ 5 exc Generic_GJ\n",
      "DB5-AVBL_GJ 3 exc Generic_GJ\n",
      "DB5-AVBR_GJ 4 exc Generic_GJ\n",
      "DB5-DB4_GJ 5 exc Generic_GJ\n",
      "DB5-DB6_GJ 5 exc Generic_GJ\n",
      "DB6-AVBL_GJ 3 exc Generic_GJ\n",
      "DB6-AVBR_GJ 4 exc Generic_GJ\n",
      "DB6-DB5_GJ 5 exc Generic_GJ\n",
      "DB6-DB7_GJ 5 exc Generic_GJ\n",
      "DB7-AVBL_GJ 13 exc Generic_GJ\n",
      "DB7-AVBR_GJ 3 exc Generic_GJ\n",
      "DB7-DB6_GJ 5 exc Generic_GJ\n",
      "AVBR-MVL16 1 exc Acetylcholine\n",
      "DB1-MDL06 3 exc Acetylcholine\n",
      "DB1-MDL08 3 exc Acetylcholine\n",
      "DB1-MDL09 6 exc Acetylcholine\n",
      "DB1-MDR08 6 exc Acetylcholine\n",
      "DB1-MDR09 2 exc Acetylcholine\n",
      "DB2-MDL09 2 exc Acetylcholine\n",
      "DB2-MDL10 4 exc Acetylcholine\n",
      "DB2-MDL11 5 exc Acetylcholine\n",
      "DB2-MDL12 1 exc Acetylcholine\n",
      "DB2-MDR09 1 exc Acetylcholine\n",
      "DB2-MDR10 6 exc Acetylcholine\n",
      "DB2-MDR11 8 exc Acetylcholine\n",
      "DB3-MDL11 6 exc Acetylcholine\n",
      "DB3-MDL12 1 exc Acetylcholine\n",
      "DB3-MDL13 3 exc Acetylcholine\n",
      "DB3-MDL14 1 exc Acetylcholine\n",
      "DB3-MDR11 2 exc Acetylcholine\n",
      "DB3-MDR12 13 exc Acetylcholine\n",
      "DB3-MDR13 1 exc Acetylcholine\n",
      "DB4-MDL13 4 exc Acetylcholine\n",
      "DB4-MDL14 1 exc Acetylcholine\n",
      "DB4-MDL15 3 exc Acetylcholine\n",
      "DB4-MDL16 3 exc Acetylcholine\n",
      "DB4-MDR13 3 exc Acetylcholine\n",
      "DB4-MDR14 5 exc Acetylcholine\n",
      "DB4-MDR15 3 exc Acetylcholine\n",
      "DB4-MDR16 3 exc Acetylcholine\n",
      "DB5-MDL14 2 exc Acetylcholine\n",
      "DB5-MDL15 2 exc Acetylcholine\n",
      "DB5-MDL16 2 exc Acetylcholine\n",
      "DB5-MDL17 2 exc Acetylcholine\n",
      "DB5-MDL18 2 exc Acetylcholine\n",
      "DB5-MDL19 2 exc Acetylcholine\n",
      "DB5-MDR14 2 exc Acetylcholine\n",
      "DB5-MDR15 2 exc Acetylcholine\n",
      "DB5-MDR16 2 exc Acetylcholine\n",
      "DB5-MDR17 2 exc Acetylcholine\n",
      "DB5-MDR18 2 exc Acetylcholine\n",
      "DB5-MDR19 2 exc Acetylcholine\n",
      "DB6-MDL16 2 exc Acetylcholine\n",
      "DB6-MDL17 2 exc Acetylcholine\n",
      "DB6-MDL18 2 exc Acetylcholine\n",
      "DB6-MDL19 2 exc Acetylcholine\n",
      "DB6-MDL20 2 exc Acetylcholine\n",
      "DB6-MDL21 2 exc Acetylcholine\n",
      "DB6-MDR16 2 exc Acetylcholine\n",
      "DB6-MDR17 2 exc Acetylcholine\n",
      "DB6-MDR18 2 exc Acetylcholine\n",
      "DB6-MDR19 2 exc Acetylcholine\n",
      "DB6-MDR20 2 exc Acetylcholine\n",
      "DB6-MDR21 2 exc Acetylcholine\n",
      "DB7-MDL19 2 exc Acetylcholine\n",
      "DB7-MDL20 2 exc Acetylcholine\n",
      "DB7-MDL21 2 exc Acetylcholine\n",
      "DB7-MDL22 2 exc Acetylcholine\n",
      "DB7-MDL23 2 exc Acetylcholine\n",
      "DB7-MDL24 2 exc Acetylcholine\n",
      "DB7-MDR19 2 exc Acetylcholine\n",
      "DB7-MDR20 2 exc Acetylcholine\n",
      "DB7-MDR21 2 exc Acetylcholine\n",
      "DB7-MDR22 2 exc Acetylcholine\n",
      "DB7-MDR23 2 exc Acetylcholine\n",
      "DB7-MDR24 2 exc Acetylcholine\n",
      "MDL01-MDL02_GJ 15 exc Generic_GJ\n",
      "MDL01-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL02-MDL01_GJ 15 exc Generic_GJ\n",
      "MDL02-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL01_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL02_GJ 15 exc Generic_GJ\n",
      "MDL03-MDL04_GJ 15 exc Generic_GJ\n",
      "MDL04-MDL03_GJ 15 exc Generic_GJ\n",
      "MDL04-MDL05_GJ 15 exc Generic_GJ\n",
      "MDL05-MDL04_GJ 15 exc Generic_GJ\n",
      "MDL05-MDL06_GJ 15 exc Generic_GJ\n",
      "MDL06-MDL05_GJ 15 exc Generic_GJ\n",
      "MDL06-MDL07_GJ 15 exc Generic_GJ\n",
      "MDL07-MDL06_GJ 15 exc Generic_GJ\n",
      "MDL07-MDL08_GJ 15 exc Generic_GJ\n",
      "MDL08-MDL07_GJ 15 exc Generic_GJ\n",
      "MDL08-MDL09_GJ 15 exc Generic_GJ\n",
      "MDL09-MDL08_GJ 15 exc Generic_GJ\n",
      "MDL09-MDL10_GJ 15 exc Generic_GJ\n",
      "MDL10-MDL09_GJ 15 exc Generic_GJ\n",
      "MDL10-MDL11_GJ 15 exc Generic_GJ\n",
      "MDL11-MDL10_GJ 15 exc Generic_GJ\n",
      "MDL11-MDL12_GJ 15 exc Generic_GJ\n",
      "MDL12-MDL11_GJ 15 exc Generic_GJ\n",
      "MDL12-MDL13_GJ 15 exc Generic_GJ\n",
      "MDL13-MDL12_GJ 15 exc Generic_GJ\n",
      "MDL13-MDL14_GJ 15 exc Generic_GJ\n",
      "MDL14-MDL13_GJ 15 exc Generic_GJ\n",
      "MDL14-MDL15_GJ 15 exc Generic_GJ\n",
      "MDL15-MDL14_GJ 15 exc Generic_GJ\n",
      "MDL15-MDL16_GJ 15 exc Generic_GJ\n",
      "MDL16-MDL15_GJ 15 exc Generic_GJ\n",
      "MDL16-MDL17_GJ 15 exc Generic_GJ\n",
      "MDL17-MDL16_GJ 15 exc Generic_GJ\n",
      "MDL17-MDL18_GJ 15 exc Generic_GJ\n",
      "MDL18-MDL17_GJ 15 exc Generic_GJ\n",
      "MDL18-MDL19_GJ 15 exc Generic_GJ\n",
      "MDL19-MDL18_GJ 15 exc Generic_GJ\n",
      "MDL19-MDL20_GJ 15 exc Generic_GJ\n",
      "MDL20-MDL19_GJ 15 exc Generic_GJ\n",
      "MDL20-MDL21_GJ 15 exc Generic_GJ\n",
      "MDL21-MDL20_GJ 15 exc Generic_GJ\n",
      "MDL21-MDL22_GJ 15 exc Generic_GJ\n",
      "MDL22-MDL21_GJ 15 exc Generic_GJ\n",
      "MDL22-MDL23_GJ 15 exc Generic_GJ\n",
      "MDL23-MDL22_GJ 15 exc Generic_GJ\n",
      "MDL23-MDL24_GJ 15 exc Generic_GJ\n",
      "MDL24-MDL23_GJ 15 exc Generic_GJ\n",
      "MDR01-MDR02_GJ 15 exc Generic_GJ\n",
      "MDR01-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR02-MDR01_GJ 15 exc Generic_GJ\n",
      "MDR02-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR01_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR02_GJ 15 exc Generic_GJ\n",
      "MDR03-MDR04_GJ 15 exc Generic_GJ\n",
      "MDR04-MDR03_GJ 15 exc Generic_GJ\n",
      "MDR04-MDR05_GJ 15 exc Generic_GJ\n",
      "MDR05-MDR04_GJ 15 exc Generic_GJ\n",
      "MDR05-MDR06_GJ 15 exc Generic_GJ\n",
      "MDR06-MDR05_GJ 15 exc Generic_GJ\n",
      "MDR06-MDR07_GJ 15 exc Generic_GJ\n",
      "MDR07-MDR06_GJ 15 exc Generic_GJ\n",
      "MDR07-MDR08_GJ 15 exc Generic_GJ\n",
      "MDR08-MDR07_GJ 15 exc Generic_GJ\n",
      "MDR08-MDR09_GJ 15 exc Generic_GJ\n",
      "MDR09-MDR08_GJ 15 exc Generic_GJ\n",
      "MDR09-MDR10_GJ 15 exc Generic_GJ\n",
      "MDR10-MDR09_GJ 15 exc Generic_GJ\n",
      "MDR10-MDR11_GJ 15 exc Generic_GJ\n",
      "MDR11-MDR10_GJ 15 exc Generic_GJ\n",
      "MDR11-MDR12_GJ 15 exc Generic_GJ\n",
      "MDR12-MDR11_GJ 15 exc Generic_GJ\n",
      "MDR12-MDR13_GJ 15 exc Generic_GJ\n",
      "MDR13-MDR12_GJ 15 exc Generic_GJ\n",
      "MDR13-MDR14_GJ 15 exc Generic_GJ\n",
      "MDR14-MDR13_GJ 15 exc Generic_GJ\n",
      "MDR14-MDR15_GJ 15 exc Generic_GJ\n",
      "MDR15-MDR14_GJ 15 exc Generic_GJ\n",
      "MDR15-MDR16_GJ 15 exc Generic_GJ\n",
      "MDR16-MDR15_GJ 15 exc Generic_GJ\n",
      "MDR16-MDR17_GJ 15 exc Generic_GJ\n",
      "MDR17-MDR16_GJ 15 exc Generic_GJ\n",
      "MDR17-MDR18_GJ 15 exc Generic_GJ\n",
      "MDR18-MDR17_GJ 15 exc Generic_GJ\n",
      "MDR18-MDR19_GJ 15 exc Generic_GJ\n",
      "MDR19-MDR18_GJ 15 exc Generic_GJ\n",
      "MDR19-MDR20_GJ 15 exc Generic_GJ\n",
      "MDR20-MDR19_GJ 15 exc Generic_GJ\n",
      "MDR20-MDR21_GJ 15 exc Generic_GJ\n",
      "MDR21-MDR20_GJ 15 exc Generic_GJ\n",
      "MDR21-MDR22_GJ 15 exc Generic_GJ\n",
      "MDR22-MDR21_GJ 15 exc Generic_GJ\n",
      "MDR22-MDR23_GJ 15 exc Generic_GJ\n",
      "MDR23-MDR22_GJ 15 exc Generic_GJ\n",
      "MDR23-MDR24_GJ 15 exc Generic_GJ\n",
      "MDR24-MDR23_GJ 15 exc Generic_GJ\n",
      "MVL01-MVL02_GJ 15 exc Generic_GJ\n",
      "MVL01-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL02-MVL01_GJ 15 exc Generic_GJ\n",
      "MVL02-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL01_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL02_GJ 15 exc Generic_GJ\n",
      "MVL03-MVL04_GJ 15 exc Generic_GJ\n",
      "MVL04-MVL03_GJ 15 exc Generic_GJ\n",
      "MVL04-MVL05_GJ 15 exc Generic_GJ\n",
      "MVL05-MVL04_GJ 15 exc Generic_GJ\n",
      "MVL05-MVL06_GJ 15 exc Generic_GJ\n",
      "MVL06-MVL05_GJ 15 exc Generic_GJ\n",
      "MVL06-MVL07_GJ 15 exc Generic_GJ\n",
      "MVL07-MVL06_GJ 15 exc Generic_GJ\n",
      "MVL07-MVL08_GJ 15 exc Generic_GJ\n",
      "MVL08-MVL07_GJ 15 exc Generic_GJ\n",
      "MVL08-MVL09_GJ 15 exc Generic_GJ\n",
      "MVL09-MVL08_GJ 15 exc Generic_GJ\n",
      "MVL09-MVL10_GJ 15 exc Generic_GJ\n",
      "MVL09-MVR08_GJ 2 exc Generic_GJ\n",
      "MVL10-MVL09_GJ 15 exc Generic_GJ\n",
      "MVL10-MVL11_GJ 15 exc Generic_GJ\n",
      "MVL11-MVL10_GJ 15 exc Generic_GJ\n",
      "MVL11-MVL12_GJ 15 exc Generic_GJ\n",
      "MVL12-MVL11_GJ 15 exc Generic_GJ\n",
      "MVL12-MVL13_GJ 15 exc Generic_GJ\n",
      "MVL13-MVL12_GJ 15 exc Generic_GJ\n",
      "MVL13-MVL14_GJ 15 exc Generic_GJ\n",
      "MVL14-MVL13_GJ 15 exc Generic_GJ\n",
      "MVL14-MVL15_GJ 15 exc Generic_GJ\n",
      "MVL15-MVL14_GJ 15 exc Generic_GJ\n",
      "MVL15-MVL16_GJ 15 exc Generic_GJ\n",
      "MVL16-MVL15_GJ 15 exc Generic_GJ\n",
      "MVL16-MVL17_GJ 15 exc Generic_GJ\n",
      "MVL17-MVL16_GJ 15 exc Generic_GJ\n",
      "MVL17-MVL18_GJ 15 exc Generic_GJ\n",
      "MVL18-MVL17_GJ 15 exc Generic_GJ\n",
      "MVL18-MVL19_GJ 15 exc Generic_GJ\n",
      "MVL19-MVL18_GJ 15 exc Generic_GJ\n",
      "MVL19-MVL20_GJ 15 exc Generic_GJ\n",
      "MVL20-MVL19_GJ 15 exc Generic_GJ\n",
      "MVL20-MVL21_GJ 15 exc Generic_GJ\n",
      "MVL21-MVL20_GJ 15 exc Generic_GJ\n",
      "MVL21-MVL22_GJ 15 exc Generic_GJ\n",
      "MVL22-MVL21_GJ 15 exc Generic_GJ\n",
      "MVL22-MVL23_GJ 15 exc Generic_GJ\n",
      "MVL23-MVL22_GJ 15 exc Generic_GJ\n",
      "MVR01-MVR02_GJ 15 exc Generic_GJ\n",
      "MVR01-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR02-MVR01_GJ 15 exc Generic_GJ\n",
      "MVR02-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR01_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR02_GJ 15 exc Generic_GJ\n",
      "MVR03-MVR04_GJ 15 exc Generic_GJ\n",
      "MVR04-MVR03_GJ 15 exc Generic_GJ\n",
      "MVR04-MVR05_GJ 15 exc Generic_GJ\n",
      "MVR05-MVR04_GJ 15 exc Generic_GJ\n",
      "MVR05-MVR06_GJ 15 exc Generic_GJ\n",
      "MVR06-MVR05_GJ 15 exc Generic_GJ\n",
      "MVR06-MVR07_GJ 15 exc Generic_GJ\n",
      "MVR07-MVR06_GJ 15 exc Generic_GJ\n",
      "MVR07-MVR08_GJ 15 exc Generic_GJ\n",
      "MVR08-MVL09_GJ 2 exc Generic_GJ\n",
      "MVR08-MVR07_GJ 15 exc Generic_GJ\n",
      "MVR08-MVR09_GJ 15 exc Generic_GJ\n",
      "MVR09-MVR08_GJ 15 exc Generic_GJ\n",
      "MVR09-MVR10_GJ 15 exc Generic_GJ\n",
      "MVR10-MVR09_GJ 15 exc Generic_GJ\n",
      "MVR10-MVR11_GJ 15 exc Generic_GJ\n",
      "MVR11-MVR10_GJ 15 exc Generic_GJ\n",
      "MVR11-MVR12_GJ 15 exc Generic_GJ\n",
      "MVR12-MVR11_GJ 15 exc Generic_GJ\n",
      "MVR12-MVR13_GJ 15 exc Generic_GJ\n",
      "MVR13-MVR12_GJ 15 exc Generic_GJ\n",
      "MVR13-MVR14_GJ 15 exc Generic_GJ\n",
      "MVR14-MVR13_GJ 15 exc Generic_GJ\n",
      "MVR14-MVR15_GJ 15 exc Generic_GJ\n",
      "MVR15-MVR14_GJ 15 exc Generic_GJ\n",
      "MVR15-MVR16_GJ 15 exc Generic_GJ\n",
      "MVR16-MVR15_GJ 15 exc Generic_GJ\n",
      "MVR16-MVR17_GJ 15 exc Generic_GJ\n",
      "MVR17-MVR16_GJ 15 exc Generic_GJ\n",
      "MVR17-MVR18_GJ 15 exc Generic_GJ\n",
      "MVR18-MVR17_GJ 15 exc Generic_GJ\n",
      "MVR18-MVR19_GJ 15 exc Generic_GJ\n",
      "MVR19-MVR18_GJ 15 exc Generic_GJ\n",
      "MVR19-MVR20_GJ 15 exc Generic_GJ\n",
      "MVR20-MVR19_GJ 15 exc Generic_GJ\n",
      "MVR20-MVR21_GJ 15 exc Generic_GJ\n",
      "MVR21-MVR20_GJ 15 exc Generic_GJ\n",
      "MVR21-MVR22_GJ 15 exc Generic_GJ\n",
      "MVR22-MVR21_GJ 15 exc Generic_GJ\n",
      "MVR22-MVR23_GJ 15 exc Generic_GJ\n",
      "MVR23-MVR22_GJ 15 exc Generic_GJ\n",
      "c302      >>>  Writing generated network to: /home/developer/forks/CElegansNeuroML/CElegans/pythonScripts/c302/examples/c302_C2_AVB_DB.nml\n",
      "Validating examples/c302_C2_AVB_DB.nml against /usr/local/lib/python2.7/dist-packages/neuroml/nml/NeuroML_v2beta4.xsd\n",
      "It's valid!\n",
      "(Re)written network file to: examples/c302_C2_AVB_DB.nml\n",
      "c302      >>>  Finished simulation of LEMS_c302_C2_AVB_DB.xml and have reloaded results\n",
      "c302      >>>  Reloaded data: ['MVL16/0/GenericMuscleCell/caConc', 'MDR14/0/GenericMuscleCell/caConc', 'MDR20/0/GenericMuscleCell/caConc', 'MDR14/0/GenericMuscleCell/v', 'MVL19/0/GenericMuscleCell/caConc', 'MVL24/0/GenericMuscleCell/v', 'MVL22/0/GenericMuscleCell/v', 'DB5/0/GenericNeuronCell/v', 'MVR02/0/GenericMuscleCell/v', 'MDR21/0/GenericMuscleCell/caConc', 'MDL08/0/GenericMuscleCell/v', 'MVR09/0/GenericMuscleCell/caConc', 'MDR10/0/GenericMuscleCell/v', 'MVL07/0/GenericMuscleCell/v', 'MVR05/0/GenericMuscleCell/v', 'MVL24/0/GenericMuscleCell/caConc', 'MDR18/0/GenericMuscleCell/v', 'MDR04/0/GenericMuscleCell/caConc', 'MVL10/0/GenericMuscleCell/v', 'MDR13/0/GenericMuscleCell/caConc', 'MDR05/0/GenericMuscleCell/caConc', 'MVL15/0/GenericMuscleCell/v', 'MDL05/0/GenericMuscleCell/caConc', 'MDL09/0/GenericMuscleCell/v', 'MVR04/0/GenericMuscleCell/v', 'MVL05/0/GenericMuscleCell/v', 'MVR19/0/GenericMuscleCell/caConc', 'MVR10/0/GenericMuscleCell/v', 'MDR17/0/GenericMuscleCell/v', 'MDL13/0/GenericMuscleCell/v', 'MDL23/0/GenericMuscleCell/v', 'MDR03/0/GenericMuscleCell/caConc', 'MVL07/0/GenericMuscleCell/caConc', 'MDL06/0/GenericMuscleCell/v', 'MDR18/0/GenericMuscleCell/caConc', 'MDL11/0/GenericMuscleCell/v', 'MVL12/0/GenericMuscleCell/v', 'MVR01/0/GenericMuscleCell/v', 'DB6/0/GenericNeuronCell/v', 'MDR19/0/GenericMuscleCell/v', 'MDL16/0/GenericMuscleCell/caConc', 'DB4/0/GenericNeuronCell/v', 'MDL24/0/GenericMuscleCell/v', 'MDL02/0/GenericMuscleCell/caConc', 'MVR21/0/GenericMuscleCell/v', 'DB1/0/GenericNeuronCell/v', 'MVL01/0/GenericMuscleCell/caConc', 'MVL06/0/GenericMuscleCell/caConc', 'MVL06/0/GenericMuscleCell/v', 'MDR13/0/GenericMuscleCell/v', 'DB4/0/GenericNeuronCell/caConc', 'MDL19/0/GenericMuscleCell/caConc', 'MDL16/0/GenericMuscleCell/v', 'MDR11/0/GenericMuscleCell/caConc', 'MDR04/0/GenericMuscleCell/v', 'AVBL/0/GenericNeuronCell/v', 'MVL20/0/GenericMuscleCell/caConc', 'DB3/0/GenericNeuronCell/caConc', 'MDR16/0/GenericMuscleCell/caConc', 'MDR05/0/GenericMuscleCell/v', 'DB5/0/GenericNeuronCell/caConc', 'MVR23/0/GenericMuscleCell/caConc', 'MDR09/0/GenericMuscleCell/v', 'MVL14/0/GenericMuscleCell/v', 'MDR15/0/GenericMuscleCell/v', 'MVR22/0/GenericMuscleCell/v', 'MVR14/0/GenericMuscleCell/v', 'MDL20/0/GenericMuscleCell/v', 'MVR18/0/GenericMuscleCell/v', 'MDL17/0/GenericMuscleCell/v', 'MVL22/0/GenericMuscleCell/caConc', 'MVL03/0/GenericMuscleCell/caConc', 'MDR02/0/GenericMuscleCell/v', 'MVL04/0/GenericMuscleCell/v', 'MDL08/0/GenericMuscleCell/caConc', 'MVR19/0/GenericMuscleCell/v', 'MVR05/0/GenericMuscleCell/caConc', 'MDL06/0/GenericMuscleCell/caConc', 'MVL17/0/GenericMuscleCell/v', 'MDL03/0/GenericMuscleCell/caConc', 'MVL19/0/GenericMuscleCell/v', 'MDR12/0/GenericMuscleCell/v', 'MVR23/0/GenericMuscleCell/v', 'MDL17/0/GenericMuscleCell/caConc', 'MVL23/0/GenericMuscleCell/v', 'MVR16/0/GenericMuscleCell/caConc', 'MDR15/0/GenericMuscleCell/caConc', 'DB7/0/GenericNeuronCell/v', 'MVL02/0/GenericMuscleCell/v', 'MVR17/0/GenericMuscleCell/v', 'MDL18/0/GenericMuscleCell/v', 'MVR07/0/GenericMuscleCell/v', 'MDL14/0/GenericMuscleCell/caConc', 'MVL17/0/GenericMuscleCell/caConc', 'MDL23/0/GenericMuscleCell/caConc', 'MVL18/0/GenericMuscleCell/v', 'MVL15/0/GenericMuscleCell/caConc', 'MVL23/0/GenericMuscleCell/caConc', 'MVR20/0/GenericMuscleCell/caConc', 'MVL09/0/GenericMuscleCell/v', 'MVR06/0/GenericMuscleCell/v', 'MDL01/0/GenericMuscleCell/caConc', 'MDR12/0/GenericMuscleCell/caConc', 'MVL08/0/GenericMuscleCell/caConc', 'MDR10/0/GenericMuscleCell/caConc', 'DB7/0/GenericNeuronCell/caConc', 'MDR23/0/GenericMuscleCell/caConc', 'DB1/0/GenericNeuronCell/caConc', 'MVR16/0/GenericMuscleCell/v', 'MDL18/0/GenericMuscleCell/caConc', 'MDL10/0/GenericMuscleCell/caConc', 'MDL07/0/GenericMuscleCell/caConc', 'MDL12/0/GenericMuscleCell/caConc', 'MDR20/0/GenericMuscleCell/v', 'MDR23/0/GenericMuscleCell/v', 'MDL22/0/GenericMuscleCell/caConc', 'MVL10/0/GenericMuscleCell/caConc', 'MVR08/0/GenericMuscleCell/v', 'MVR20/0/GenericMuscleCell/v', 'MDL03/0/GenericMuscleCell/v', 'MVL09/0/GenericMuscleCell/caConc', 'MVL21/0/GenericMuscleCell/caConc', 'MVL20/0/GenericMuscleCell/v', 't', 'MVL05/0/GenericMuscleCell/caConc', 'MDR11/0/GenericMuscleCell/v', 'MVL13/0/GenericMuscleCell/caConc', 'MDL02/0/GenericMuscleCell/v', 'MDR06/0/GenericMuscleCell/v', 'MDR01/0/GenericMuscleCell/caConc', 'MDR07/0/GenericMuscleCell/caConc', 'MVR11/0/GenericMuscleCell/caConc', 'MVR18/0/GenericMuscleCell/caConc', 'MDL11/0/GenericMuscleCell/caConc', 'MVL03/0/GenericMuscleCell/v', 'MDL10/0/GenericMuscleCell/v', 'MVR09/0/GenericMuscleCell/v', 'MDL04/0/GenericMuscleCell/v', 'DB2/0/GenericNeuronCell/caConc', 'MVL02/0/GenericMuscleCell/caConc', 'MVL14/0/GenericMuscleCell/caConc', 'MDR17/0/GenericMuscleCell/caConc', 'DB2/0/GenericNeuronCell/v', 'MDL13/0/GenericMuscleCell/caConc', 'MDR06/0/GenericMuscleCell/caConc', 'MDR03/0/GenericMuscleCell/v', 'MDL22/0/GenericMuscleCell/v', 'MDR08/0/GenericMuscleCell/v', 'MDL01/0/GenericMuscleCell/v', 'MVL01/0/GenericMuscleCell/v', 'MVR15/0/GenericMuscleCell/v', 'MVL04/0/GenericMuscleCell/caConc', 'AVBL/0/GenericNeuronCell/caConc', 'DB3/0/GenericNeuronCell/v', 'MVL18/0/GenericMuscleCell/caConc', 'MDL09/0/GenericMuscleCell/caConc', 'MDL20/0/GenericMuscleCell/caConc', 'MVR11/0/GenericMuscleCell/v', 'MVL12/0/GenericMuscleCell/caConc', 'MVL16/0/GenericMuscleCell/v', 'AVBR/0/GenericNeuronCell/v', 'DB6/0/GenericNeuronCell/caConc', 'MVR06/0/GenericMuscleCell/caConc', 'MVR02/0/GenericMuscleCell/caConc', 'MDL04/0/GenericMuscleCell/caConc', 'MDL21/0/GenericMuscleCell/v', 'MVR07/0/GenericMuscleCell/caConc', 'MDR24/0/GenericMuscleCell/v', 'MDR09/0/GenericMuscleCell/caConc', 'MVL08/0/GenericMuscleCell/v', 'MVR01/0/GenericMuscleCell/caConc', 'MVR03/0/GenericMuscleCell/v', 'MVR17/0/GenericMuscleCell/caConc', 'MVR22/0/GenericMuscleCell/caConc', 'MVR13/0/GenericMuscleCell/v', 'MVR21/0/GenericMuscleCell/caConc', 'MVR04/0/GenericMuscleCell/caConc', 'MDL05/0/GenericMuscleCell/v', 'MDL24/0/GenericMuscleCell/caConc', 'MDL15/0/GenericMuscleCell/caConc', 'MVR10/0/GenericMuscleCell/caConc', 'MDL14/0/GenericMuscleCell/v', 'MDR19/0/GenericMuscleCell/caConc', 'MDR07/0/GenericMuscleCell/v', 'MDL21/0/GenericMuscleCell/caConc', 'MVL21/0/GenericMuscleCell/v', 'MDR01/0/GenericMuscleCell/v', 'MVR12/0/GenericMuscleCell/v', 'MVR13/0/GenericMuscleCell/caConc', 'MVL11/0/GenericMuscleCell/v', 'MDR02/0/GenericMuscleCell/caConc', 'MDR24/0/GenericMuscleCell/caConc', 'MVL11/0/GenericMuscleCell/caConc', 'MDL07/0/GenericMuscleCell/v', 'MVR08/0/GenericMuscleCell/caConc', 'MDR22/0/GenericMuscleCell/caConc', 'MVR14/0/GenericMuscleCell/caConc', 'MVR12/0/GenericMuscleCell/caConc', 'MVL13/0/GenericMuscleCell/v', 'MDL15/0/GenericMuscleCell/v', 'MVR03/0/GenericMuscleCell/caConc', 'MDR08/0/GenericMuscleCell/caConc', 'MDR22/0/GenericMuscleCell/v', 'MDL19/0/GenericMuscleCell/v', 'MDR16/0/GenericMuscleCell/v', 'MDR21/0/GenericMuscleCell/v', 'MDL12/0/GenericMuscleCell/v', 'AVBR/0/GenericNeuronCell/caConc', 'MVR15/0/GenericMuscleCell/caConc']\n",
      "c302      >>>  All cells: ['DB7', 'DB6', 'DB5', 'DB4', 'DB3', 'DB2', 'DB1', 'AVBR', 'AVBL']\n",
      "c302      >>>  Plotting neuron voltages\n",
      "c302      >>>  Generating plots for: Membrane potentials of 9 neuron(s) (AVB_DB C2)\n",
      "c302      >>>  Plotting muscle voltages\n",
      "c302      >>>  Generating plots for: Membrane potentials of 95 muscle(s) (AVB_DB C2)\n"
     ]
    },
    {
     "data": {
      "image/png": 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SoaouTnJ+kmvG4++XZF+S+yd5UpKvSXKPJGd39/ces5oCAADAyWQbDoqwaneG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\nSZKkgXgTQZIkSZIkDeT/AeUIt0q8QRTFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe7e5b79650>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ZEy2L6+7uJlwCAAAAgJQxK3C2OKQO4VLmhJKMziUAAAAASKEgYFkc0odwKWs8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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe7e35f4f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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I4C7AixY3fEmSJEmStNm6TIv48DwDkyRJkiRpO9qNhTh3RVrEkRgS+ps9iFUc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\nBxckSZIkSdKa/P/YFPEb/X232wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe7e58919d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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x5zCp/6Qur2OSLsn6dpJ1bSR3tJPc0eYt9e24TXEcp5VkSSPJWCNOSSNOtAU3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\nWUK1s+E9dIx0AjASqeAwkiRJkiRpLrOEamfDfZSr88nqwzzxSS8oOo0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cILLzgEAgHF5/Mpz/0HKm9kYTQayWHDhrmGDBniMpvNJADA8OHD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\nWfRkzGy7z+OyoKhf6/aePy9atEh86dIl9pYtW2jlANB/Y2bbfTyz6Mpr5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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe7e345ebd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from runAndPlot import run_c302\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt \n",
    "plt.rcParams['figure.figsize'] = (20.0, 10.0)\n",
    "#plt.rcParams[\"font.size\"] = \"80\"\n",
    "#plt.rcParams['legend.fontsize'] = \"80\"\n",
    "cells, cells_to_stimulate, params, muscles = run_c302('AVB_DB','C2','',4000,0.05,'jNeuroML_NEURON',verbose=False, plot_ca=False, data_reader=\"UpdatedSpreadsheetDataReader\", config_package=\"notebooks.configs.AVB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
